thresholding is performed on an inputted pixel value using a corrected threshold value in a thresholding unit, and a binarized pixel value is output. The output is inverted, and from the inverted output the threshold value used for the thresholding is subtracted, and the resultant value is distributed to threshold values used for processing of the surrounding pixels. At this time, an input value is added to the value to be distributed (feedback value). Then, in the thresholding of the next pixel, the input value is subtracted from the distributed value, and the result is subtracted from an initial threshold value to derive a value which becomes a threshold value to be used in the binarization. When the input value changes, there is an effect of canceling out the change so that the edge can be weakened.
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9. An image processing method, comprising the steps of:
successively inputting a first image signal representing each pixel;
performing thresholding on said inputted first image signal using a prescribed threshold value; and
distributing a value used in the thresholding in a succeeding pixel, wherein
said thresholding step is done based on the value distributed by said distributing unit and on a specific value determined for each pixel, and
said distributing step calculates a value to be distributed to the succeeding pixel based on an input signal and an output signal of said thresholding step and on the specific value determined for each pixel.
1. An image processing apparatus comprising:
an input unit for successively receiving as input a first image signal representing each pixel;
a thresholding unit for performing thresholding on said inputted first image signal using a prescribed threshold value; and
a distributing unit for distributing a value used in the thresholding in a succeeding pixel, wherein
said thresholding unit performs thresholding based on the value distributed by said distributing unit and on a specific value determined for each pixel, and
said distributing unit calculates a value to be distributed to the succeeding pixel based on an input signal and an output signal of said thresholding unit and on the specific value determined for each pixel.
2. The image processing apparatus according to
said distributing unit distributes a value obtained by adding the specific value determined for each pixel to a result of operation based on a threshold value used in said thresholding unit and on an output signal from said thresholding unit, and
said thresholding unit generates a threshold value based on a result obtained by subtracting the specific value determined for each pixel from the value distributed by said distributing unit, and performs thresholding.
3. The image processing apparatus according to
said distributing unit distributes a value obtained by subtracting the specific value determined for each pixel from a result of operation based on the input signal and the output signal of said thresholding unit, and
said thresholding unit performs thresholding after correction of the first image signal input based on a result obtained by adding the specific value determined for each pixel to the value distributed by said distributing unit.
4. The image processing apparatus according to
said distributing unit distributes a value obtained by subtracting the specific value determined for each pixel from a result of operation based on the input signal and the output signal of said thresholding unit,
said input unit successively receives as input a result obtained by subtracting the specific value determined for each pixel from the first image signal, and
said thresholding unit performs thresholding after correction of a value inputted by said input unit based on the value distributed by said distributing unit.
5. The image processing apparatus according to
the specific value determined for each pixel is a value obtained by multiplying the first image signal by a prescribed coefficient.
6. The image processing apparatus according to
a coefficient setting unit for setting said prescribed coefficient at will.
7. The image processing apparatus according to
a pattern generating unit for generating a pattern for each pixel, wherein
the specific value determined for each pixel is a value obtained by multiplying a value generated by said pattern generating unit by a prescribed coefficient.
8. The image processing apparatus according to
a coefficient setting unit for setting said prescribed coefficient at will.
10. The image processing method according to
said distributing step distributes a value obtained by adding the specific value determined for each pixel to a result of operation based on a threshold value used in said thresholding step and on an output signal from said thresholding step, and
said thresholding step generates a threshold value based on a result obtained by subtracting the specific value determined for each pixel from the value distributed by said distributing step, and performs thresholding.
11. The image processing method according to
said distributing step distributes a value obtained by subtracting the specific value determined for each pixel from a result of operation based on the input signal and the output signal of said thresholding step, and
said thresholding step performs thresholding after correction of the first image signal input based on a result obtained by adding the specific value determined for each pixel to the value distributed by said distributing step.
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This application is based on application No. 2000-293608 filed in Japan, the content of which is hereby incorporated by reference.
1. Field of the Invention
The present invention relates to an image processing apparatus, and more specifically, to an image processing apparatus that allows formation of an image in which gradations are reduced using a threshold value.
2. Description of the Related Art
Digital handling of images is currently dominant in the field of image processing. When displaying or outputting a digital image, there often is a need to express the gradations of the image using a smaller number of gradation levels due to restrictions imposed by the characteristics of the output device and so on. From the early stages of development, various image processing techniques of digital half toning, such as binarization in which the gradations are reproduced by white and black dots alone as a pseudo halftone processing, have been researched.
Among such techniques, an error diffusion method and a threshold value diffusion method, which is proposed by the applicant of the present invention in Japanese Patent Laying-Open No. 2000-165669, have proved to be particularly superior in that they maintain good resolution and gradation quality.
In the error diffusion method and the threshold value diffusion method, however, no technique had been established that enabled an edge enhancement effect to be controlled freely. Thus, the object of the present invention is to provide an image processing apparatus that allows effective control of the edge enhancement effect with extremely simple processing in a half toning process such as the error diffusion method or the threshold value diffusion method.
According to one aspect of the present invention, an image processing apparatus is provided with an input unit for successively receiving as input a first image signal representing each pixel, a thresholding unit for performing thresholding on the inputted first image signal using a prescribed threshold value, and a distributing unit for distributing a value used in the thresholding in a succeeding pixel, where the thresholding unit performs thresholding based on the value distributed by the distributing unit and on a specific value determined for each pixel, and the distributing unit calculates a value to be distributed to the succeeding pixel based on an input signal and an output signal of the thresholding unit and on the specific value determined for each pixel.
According to another aspect of the present invention, an image processing method includes the steps of successively inputting a first image signal representing each pixel, performing thresholding on the inputted first image signal using a prescribed threshold value, and distributing a value used in the thresholding in a succeeding pixel, where the step of performing thresholding is done based on the value distributed by the distributing unit and on a specific value determined for each pixel, and the step of distributing calculates a value to be distributed to the succeeding pixel based on an input signal and an output signal of the thresholding unit and on the specific value determined for each pixel.
According to these inventions, when an input value changes in the image processing, the change can be enhanced or diminished at will. Consequently, the edge enhancement effect can be controlled freely.
The foregoing and other objects, features, aspects and advantages of the present invention will become more apparent from the following detailed description of the present invention when taken in conjunction with the accompanying drawings.
Referring to the diagram, the image processing apparatus includes an input unit 501 for receiving as an input a pixel value of one pixel of a multi-value image, a subtractor 503 for subtracting a diffused error from the input pixel value, an output unit 505 for outputting an output from subtractor 503 as a corrected pixel value, a thresholding unit 507 for performing thresholding on an output of output unit 505 to form binary data, an output unit 509 for outputting an output of thresholding unit 507 as pixel data, a subtractor 511 for subtracting the output of output unit 505 from the output of thresholding unit 507, and an error memory 513 for diffusing an output result from subtractor 511 to pixels surrounding a pixel which is the object of processing (pixel of interest).
Moreover, an output of subtractor 511 shown in
Thus, as shown in
In addition, a threshold value used in thresholding unit 507 may be set by a threshold value setting unit 307.
Referring to the diagram, the image forming apparatus includes an image (pixel value) input unit 101, a thresholding unit 103, a binary image output unit 105, an inverting unit 113, an initial threshold value generating unit 107, a subtracting unit 109, a corrected threshold value output unit 111, a subtracting unit 115, a coefficient multiplying unit 117, and a correction value memory 119.
One pixel value (0 to 1) of a multi-value image is input to image input unit 101. When a multi-value image n of 256 gradations (0 to 255) is to be handled, for instance, a normalized value normalized to 0 to 1 (n/255) is input to image input unit 101. Thresholding unit 103 compares a corrected threshold value Th(x) output from corrected threshold value output unit 111 with the pixel value input to image input unit 101. When pixel value≧corrected threshold value Th(x), thresholding unit 103 outputs “1,” whereas when pixel value<corrected threshold value Th(x), thresholding unit 103 outputs “0.” Consequently, binary image output unit 105 outputs an image having binary value of “0” or “1.”
Initial threshold value generating unit 107 outputs an initial threshold value Th(x) before correction. The initial threshold value Th(x) before correction may be a constant value, or it may be varied in accordance with the position of the pixel so as to provide a dither pattern.
Subtractor 109 reads a correction value stored in correction value memory 119 which corresponds to the pixel which is the object of processing (pixel of interest), and subtracts the correction value from the initial threshold value Th(x). The result becomes the corrected threshold value Th(x).
Inverting unit 113 inverts an output from thresholding unit 103. In other words, inverting unit 113 outputs “1” when the output of thresholding unit 103 is “0,” and outputs “0” when the output is “1.”
Subtracting unit 115 subtracts corrected threshold value Th(x) from the output of inverting unit 113 and outputs the result. Coefficient multiplying unit 117 multiplies the output of subtracting unit 115 by a feed back coefficient β, which is set between 0 and 1, and outputs the result. Note that setting β=0 means that the threshold value diffusion is not to be performed.
Correction value memory 119 is a memory for distributing the output result of coefficient multiplying unit 117 to the correction values of the threshold values for pixels surrounding the pixel which is the object of processing. Referring to
[Embodiments]
First Embodiment
An image forming apparatus according to the first embodiment of the present invention will be described below. The image forming apparatus according to the first embodiment is characterized in that it performs control of the edge enhancement effect by simple processing, while at the same time, performing half toning process.
The threshold value diffusion method described as a reference example above is a superior half toning method that may replace the error diffusion method, but it has an edge enhancement effect, the degree of which could not be controlled, so that the situations in which it could be employed is disadvantageously limited. The first embodiment allows the intensity of the edge enhancement effect to be controlled freely without substantially changing the load of the threshold value diffusion method in the above reference example.
According to the first embodiment, in the threshold value diffusion method, an input value is added to a value to be fed back (a feedback value), and the result is weighted and diffused to threshold values of surrounding pixels. Then, upon using the feedback value, the input value at that time is subtracted the feedback value. When the input value does not change and remains constant, this operation involves only adding and subtracting the input value (which is constant) so that no effect is produced, but when the input value changes, the operation functions to diminish the change. Consequently, the edge can be weakened.
When the amount of the input value added to the feedback value is changed, the effect changes to the extent the amount is changed. By reversing the sign of the input value added, edge enhancement can be effected.
Referring to the diagram, in the first embodiment, a portion enclosed by the broken line of
An operation of the image processing apparatus according to the first embodiment will be described below with reference to
As shown in
As shown in
On the other hand, if the input value is reduced to 0.5 as shown in
As shown in
As shown by the above-described processing, the image processing apparatus according to the first embodiment ultimately achieves the same effect as increasing the input value in order to diminish the change in the input value when the input value changes in the direction of becoming smaller.
Conversely, the image processing apparatus according to the first embodiment achieves the same effect as decreasing the input value in order to diminish the change in the input value when the input value changes in the direction of becoming larger. With such processing, the edge can be weakened within the image which is the object of processing.
Moreover, when the value of k is changed, the intensity of the effect can be changed to the extent the value of k is changed so that the user can set the strength of the edge at will by simple processing. Conversely, when k is set to a negative value, the change of the input can be enhanced (the edge can be strengthened).
Next, a specific example of processing performed by the image processing apparatus according to the above-described embodiment will be described.
In this example, a diffusion weight coefficient shown in
A 3/40 of the feedback value would be distributed to a pixel indicated by “3,” a 2/40 of the feedback value would be distributed to a pixel indicated by “2,” and a 1/40 of the feedback value would be distributed to a pixel indicated by “1.”
In addition, in this example, initial threshold value generating unit 107 outputs a pattern of a threshold value shown in
More specifically, an initial threshold value is calculated using a formula: initial threshold value=0.5+0.05×P. Then, P in this formula is a line pattern signal to be added to a threshold value, and is calculated by the following formula:
P=((i/3+j)%4−1.5)/3
Here, (i, j) are numerical values representing a coordinate of a pixel. In addition, %4 represents a remainder produced as a result of division by 4.
Moreover, in this example, it is set such that a diffusion coefficient β=0.48, and it is adjusted such that no dot is output when the input is 0, while a dot is output when the input is not 0.
When k=0, the processing that is performed by the portion enclosed by the broken line in
As shown in
Conversely, as shown in
As described above, the first embodiment allows edge control in the threshold value diffusion method without particularly increasing the burden of processing.
Second Embodiment
The second embodiment provides for the control of the edge enhancement effect of an image processing apparatus employing an error diffusion method.
In the error diffusion method, also, the edge enhancement effect would become obvious with a broader range of error diffusion so that some measure was required. The second embodiment allows the intensity of the edge enhancement effect to be controlled freely without substantially changing the load in the error diffusion method.
In other words, in addition to the arrangement of the image processing apparatus shown in
In the second embodiment, also, the edge enhancement effect can be changed freely by changing the value of k.
Referring to
Such an operation would only involve processing of subtracting and adding a constant value when the input value does not change, so that there is no effect. When the input changes, however, such operation functions to diminish the change. As an amount of the input value added to the error is changed (that is, when the value of k is changed), the effect successively changes. In addition, by reversing the sign of k, edge enhancement can be effected.
Next, an operation of the image processing apparatus according to the second embodiment will be described with reference to
As shown in
As shown in
In other words, in the processing of
On the other hand, if the input value becomes 0.5 as shown in
Consequently, as shown in
As shown by the above processing, the second embodiment achieves the same effect as increasing the input and decreasing the change when the input value changes in the direction of becoming smaller.
Conversely, the second embodiment similarly achieves the effect of canceling out the change when the input value changes in the direction of becoming larger. Moreover, when the value of k is changed, the intensity of the effect can be changed. Conversely, when k is set to a negative value, the change can be enhanced.
Next, a specific example of processing performed by the image processing apparatus according to the second embodiment will be described.
In this example, a diffusion weight coefficient shown in
Moreover, the original image which is the object to be processed employed was the one shown in
When k=0, the processing performed by the portion indicated by the broken line in
As shown in
Conversely, as shown in
As described above, the second embodiment allows edge control in the error diffusion method without particularly increasing the burden of processing.
Further,
Third Embodiment
Referring to the diagram, the third embodiment is provided with a k determining unit 203a for setting a coefficient k in addition to the arrangement of the image processing apparatus according to the first embodiment shown in
Fourth Embodiment
Referring to the diagram, the apparatus of the fourth embodiment is provided with a pattern generating unit 221 as compared to the image processing apparatus of
According to the fourth embodiment, a pattern such as noise and so on may be added to an image. In addition, by setting k such that 0<k(<1), high frequency components of an output image can be decreased so as to cause the image to be influenced by pink noise. Moreover, when it is set such that k<0, high frequency components would increase so as to cause the image to be influenced by blue noise.
Fifth Embodiment
Sixth Embodiment
Specifically, the image processing apparatus is provided with a k multiplying unit 301 for multiplying an input from an input unit 501 by k, a (1−k) multiplying unit 321 for multiplying the input by a value of (1−k), a subtractor 323 for subtracting an error that is weighted and distributed from an output of (1−k) multiplying unit 321, a thresholding unit 507 for performing thresholding on an output of subtractor 323, an output unit 509 for outputting a result of thresholding, a subtractor 511 for subtracting the value before thresholding from a value derived after thresholding, a subtractor 305 for subtracting an output of k multiplying unit 301 from an output of subtractor 511, a threshold value generating unit 307 for generating a threshold value, and a k determining unit 301a for setting k at will.
Seventh Embodiment
Referring to the diagram, the image processing apparatus of the seventh embodiment is provided with a pattern generating unit 325 in addition to the arrangement of the image processing apparatus shown in
In this apparatus arrangement, like the image processing apparatus of
Moreover, a threshold value used in
The processing in the above-described embodiment may be performed by software or using a hardware circuit.
In addition, a program may be provided for executing the processing in the above-described embodiment, and such program may be stored in a recording medium such as a CD-ROM, a flexible disk, a hard disk, an ROM, an RAM, and a memory card, and provided to the user.
Furthermore, although the above description only illustrates the conversion from an input image of 256 gradations into an output image of two gradations, it is also possible to convert arbitrary input gradations into arbitrary output gradations using a similar technique.
Although the present invention has been described and illustrated in detail, it is clearly understood that the same is by way of illustration and example only and is not to be taken by way of limitation, the spirit and scope of the present invention being limited only by the terms of the appended claims.
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